摘要
Many enterprises and personals are inclining to outsource their data to public clouds, but security and privacy are two critical problems cannot be ignored. The door of cloud provider may be broken, and the data may also be dug into by providers to find valuable information. In this paper, a secure and efficient storage file (SES FS) system is proposed to distribute files in several clouds and allows users to search the files securely and efficiently. In the proposed system, keywords were transformed into integers and secretly shared in a defined finite field, then the shares were mapped to random numbers in specified random domain in each cloud. Files were encrypted with distinct secret key and scattered within different clouds. Information about keyword/file was secretly shared among cloud providers. Legal users can search in the clouds to find correct encrypted files and reconstruct corresponding secret key. No adversary can find or detect the real file information even they can collude all the servers. Manipulation on shares by one or more clouds can be detected with high probability. The system can also detect malicious servers through introduced virtual points. One interesting property for the scheme is that new keywords can be added easily, which is difficult and usually not efficient for many searchable symmetric encryption systems. Detailed experimental result shows, with tolerable uploading delay, the scheme exhibits excellent performance on data retrieving aspect.
出处
《国际计算机前沿大会会议论文集》
2019年第2期263-266,共4页
International Conference of Pioneering Computer Scientists, Engineers and Educators(ICPCSEE)
基金
Demonstration on the Construction of Guangdong Survey and Geomatics Industry Technology Innovation Alliance (2017B090907030)
The Demonstration of Big Data Application for Land Resource Management and Service (2015B010110006)
Qiong Huang is supported by Guangdong Natural Science Funds for Distinguished Young Scholar (No. 2014A030306021)
Guangdong Program for Special Support of Top-notch Young Professionals (No. 2015TQ01X796)
Pearl River Nova Program of Guangzhou (No. 201610010037)
and the National Natural Science Foundation of China (Nos. 61472146, 61672242).